sprs implements some sparse matrix data structures and linear algebra algorithms in pure Rust.
The API is a work in progress, and feedback on its rough edges is highly appreciated :)
- CSR/CSC matrix
- triplet matrix
- Sparse vector
- sparse matrix / sparse vector product
- sparse matrix / sparse matrix product
- sparse matrix / sparse matrix addition, subtraction
- sparse vector / sparse vector addition, subtraction, dot product
- sparse/dense matrix operations
- Outer iterator on compressed sparse matrices
- sparse vector iteration
- sparse vectors joint non zero iterations
- simple sparse Cholesky decomposition (requires opting into an LGPL license)
- sparse triangular solves with dense right-hand side
Matrix construction
use sprs::{CsMat, CsMatOwned, CsVec};
let eye : CsMatOwned<f64> = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
vec![0, 2, 4, 5],
vec![0, 1, 0, 2, 2],
vec![1., 2., 3., 4., 5.]);Matrix vector multiplication
use sprs::{CsMat, CsVec};
let eye = CsMat::eye(5);
let x = CsVec::new(5, vec![0, 2, 4], vec![1., 2., 3.]);
let y = &eye * &x;
assert_eq!(x, y);Matrix matrix multiplication, addition
use sprs::{CsMat, CsVec};
let eye = CsMat::eye(3);
let a = CsMat::new_csc((3, 3),
vec![0, 2, 4, 5],
vec![0, 1, 0, 2, 2],
vec![1., 2., 3., 4., 5.]);
let b = &eye * &a;
assert_eq!(a, b.to_csr());For a more complete example, be sure to check out the heat diffusion example.
Documentation is available at docs.rs.
See the changelog.
Licensed under either of
- Apache License, Version 2.0, (./LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (./LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.